Exactness Completion Audit

This audit answers one question: are the posttrainllm docs now exact enough to be trusted as the operating system for the project?

Completion Standard

The docs pass is complete when the repository has:

1. A current docs golden path.
2. A structured attempt ledger with evidence, final status, confidence, lesson, and next action, with no unresolved not-tried state.
3. A human-readable ledger synced to the structured ledger.
4. A coverage audit that distinguishes attempts, technique inventory, narrative history, and learning notes.
5. A structured treatment of the broad audit_2026.md technique audit.
6. Factory run/report schemas that require exactness fields before publishing.
7. A learning path and progress tracker tied to the active factory loop.
8. Smoke checks that fail when the above surfaces drift.
9. A completion validator that rejects unresolved attempts, uncovered techniques, dangling learning paths, or missing public surfaces.

Evidence

Current Counts

Structured attempt ledger:

Technique audit inventory:

Closed Boundary

There is no implicit documentation-hardening backlog after this pass. Future automation, provenance fields, or learning checkpoints begin only when the owner opens a fresh experiment after the learning phase. Historical absences remain explicit limitations rather than AI follow-up work.

Verification

The current proof set is:

bash evals/attempt-ledger-smoke.sh
bash evals/technique-inventory-smoke.sh
bash evals/docs-world-class-smoke.sh
bash evals/factory-publish-check-smoke.sh
bash evals/learning-roadmap-smoke.sh
bash evals/project-completion-smoke.sh
python3 -m py_compile scripts/docs-checks/check_attempt_ledger.py scripts/docs-checks/check_docs_world_class.py scripts/factory/check_factory_run_publish.py scripts/docs-checks/check_learning_roadmap.py scripts/docs-checks/check_technique_inventory.py scripts/sql/render_sql_factory_run.py
git diff --check
cd browser && npm run build

Verdict

The docs are now exact enough to operate from:

• attempts are structured and confidence-labeled;
• broad technique rows are classified instead of misreported as attempts;
• old narrative surfaces have explicit treatment rules;
• factory reports must carry exactness fields;
• the learning path is tied to the same factory loop;
• smoke checks guard the core docs surfaces.

Any future automation or provenance work begins under a fresh owner-selected experiment; it is not unfinished work in this closed project.